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mcp-paperless-ngx

mcp-paperless-ngx

by tobee89
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Get AI filing suggestions

get_document_ai_suggestions
Read-onlyIdempotent

Retrieve AI-generated document suggestions by ID from the Paperless-ngx LLM backend. Works only when AI features are enabled server-side; otherwise returns an expected 404.

Instructions

Suggestions from the instance's configured LLM backend (Paperless-ngx 3.x, only if AI features are enabled server-side). Returns 404 or an error when AI is disabled — that is expected, not a bug.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "get_document_ai_suggestions"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds meaningful behavioral context beyond that: the tool is tied to a specific version (Paperless-ngx 3.x), depends on server-side AI features, and will return 404/error when disabled. This failure-mode disclosure is valuable and not present in annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, zero waste. The primary behavior is stated first, followed by a critical caveat about expected failure modes. All information is relevant and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given one simple parameter, no output schema, and strong annotations covering safety, the description is nearly complete. It covers the feature dependency, version, and expected error behavior. The only gap is that it does not describe the shape of a successful response, but this is minor for such a simple read-only tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the single parameter 'id' is a standard integer with exclusiveMinimum. The description does not explicitly say id refers to a document ID, though the tool name makes it inferable. The description adds no parameter-level semantics, but the meaning is clear enough given the context, so a 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The title 'Get AI filing suggestions' and description 'Suggestions from the instance's configured LLM backend' clearly state the core function and resource. It differentiates from the sibling get_document_suggestions by the 'AI' and 'LLM backend' qualifiers, though it does not explicitly name the alternative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

States a clear precondition: 'only if AI features are enabled server-side.' It also gives explicit guidance on the expected 404/error result when AI is disabled, telling the agent this is normal. It does not explicitly mention the sibling get_document_suggestions or say 'use this instead when...', but the conditional context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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